Multifactor-dimensionality reduction reveals high-order interactions among estrogen-metabolism genes in sporadic breast cancer.

Ritchie MD, Hahn LW, Roodi N, Bailey LR, Dupont WD, Parl FF, Moore JH
Am J Hum Genet. 2001 69 (1): 138-47

PMID: 11404819 · PMCID: PMC1226028 · DOI:10.1086/321276

One of the greatest challenges facing human geneticists is the identification and characterization of susceptibility genes for common complex multifactorial human diseases. This challenge is partly due to the limitations of parametric-statistical methods for detection of gene effects that are dependent solely or partially on interactions with other genes and with environmental exposures. We introduce multifactor-dimensionality reduction (MDR) as a method for reducing the dimensionality of multilocus information, to improve the identification of polymorphism combinations associated with disease risk. The MDR method is nonparametric (i.e., no hypothesis about the value of a statistical parameter is made), is model-free (i.e., it assumes no particular inheritance model), and is directly applicable to case-control and discordant-sib-pair studies. Using simulated case-control data, we demonstrate that MDR has reasonable power to identify interactions among two or more loci in relatively small samples. When it was applied to a sporadic breast cancer case-control data set, in the absence of any statistically significant independent main effects, MDR identified a statistically significant high-order interaction among four polymorphisms from three different estrogen-metabolism genes. To our knowledge, this is the first report of a four-locus interaction associated with a common complex multifactorial disease.

MeSH Terms (23)

Alleles Aryl Hydrocarbon Hydroxylases Breast Neoplasms Case-Control Studies Chromosome Mapping Computer Simulation Cytochrome P-450 CYP1A1 Cytochrome P-450 CYP1B1 Cytochrome P-450 Enzyme System Estrogens European Continental Ancestry Group Female Gene Frequency Genetic Predisposition to Disease Genotype Humans Matched-Pair Analysis Methyltransferases Mutation, Missense Polymorphism, Genetic Reproducibility of Results Sample Size Statistics, Nonparametric

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